Design of Experiments

This page offers a flavour of the research being done in the Probability and Statistics Group at the University of Manchester in the field of Experimental Design.

The Group has active research projects in the areas of modern experimental design, encompassing theoretical work on optimality motivated by practical problems through to algorithmic methods for obtaining non-standard designs. Following the recent publication of the influential book on optimal experimental designs (authors A. C. Atkinson, A. N. Donev and R. D. Tobias), A. N. Donev has continued to develop key theoretical results in the area of optimal experimental designs. He maintains strong interest in the design of experiments with both qualitative and quantitative factors, for example when fitting nonlinear models is required and optimal Bayesian experimental designs might be useful. Current research focuses on biological experiments, high throughput screening, mixture experiments and when there might be errors in setting the factor levels. Work on problems which is expected to lead to key theoretical results includes also the design of experiments for multivariate response exploration, nonlinear random effects models, confirmatory experiments and process monitoring.